Embedded Files
⭐ Connecting Data Literacy to Essential Key Concepts ⭐️
Exploring Data Literacy offers authentic opportunities to revisit the Essential Key Concepts of Decimal Reasoning and Operations and Proportional Reasoning:
B1.5 → Read, represent, compare, and order decimal numbers up to hundredths
Students use decimal reasoning to interpret relative-frequency tables that report decimals and compare data proportions in meaningful ways
B1.7 → Equivalences among fractions, decimal hundredths, and percents
When creating infographics, students convert data from fractions to decimals (or vice versa) to make the information more accessible across different representations
B2.3 → Mutliply whole numbers by 0.1 and 0.01 and estimate sums and differences of decimal numbers
While organizing and analysing decimal-based data, students reason in their heads (e.g., 0.25 + 0.75) to quickly calculate combined frequencies or to check no decimals were misplaced
B2.9 → Represent and create equivalent ratios and rates
Students use fractional and proportional reasoning to express relative frequencies (e.g., "15 out of 60" as 1/4 or 25%) and choose the right data display based on proportional comparisons
Expectation Cluster
Expectation Cluster
D1.1 explain the importance of various sampling techniques for collecting a sample of data that is representative of a population
D1.2 collect data, using appropriate sampling techniques as needed, to answer questions of interest about a population, and organize the data in relative-frequency tables
D1.3 select from among a variety of graphs, including stacked-bar graphs, the type of graph best suited to represent various sets of data; display the data in the graphs with proper sources, titles, and labels, and appropriate scales; and justify their choice of graphs
D1.4 create an infographic about a data set, representing the data in appropriate ways, including in relative-frequency tables and stacked-bar graphs, and incorporating any other relevant information that helps to tell a story about the data
Mathematical Modelling is a key process expectation that connects across multiple strands. Opportunities to engage students in modelling may arise naturally within rich, real-world contexts — for example, in financial literacy (e.g., creating a budget), measurement (e.g., designing a garden space), or data (e.g., interpreting results from a student survey).
We recommend using open-ended tasks where students define problems, make decisions, and justify their thinking — even in informal ways — as early steps toward developing modelling skills.
See our Mathematical Modelling page for more information.
Process Expectation Focus: Communicating, Selecting Tools and Strategies
Organize your observations of student learning related to the key concepts and skills for this topic:
Explore a menu of possible MathUP lessons, Building Fluency lessons, problems, explorations and games.
During this topic, pay attention to the students' ability to develop self-awareness and sense of identity.
Do students perceive themselves as capable math learners?
Can students describe some of their mathematical strengths?
Do students demonstrate ownership of their learning? (e.g. using the resources and tools in the classroom, asking questions, using feedback to set a personal learning goal, taking risks in their learning)
Models and Tools
Models and Tools
Concrete Learning Resources Tools:
grid paper
snap cubes
tiles
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